Triple
T15126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivy League |
E301
|
entity |
| Predicate | hasCommonEntranceExamUsage |
P260
|
FINISHED |
| Object | standardized tests such as SAT and ACT |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: standardized tests such as SAT and ACT | Statement: [Ivy League, hasCommonEntranceExamUsage, standardized tests such as SAT and ACT]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonEntranceExamUsage Context triple: [Ivy League, hasCommonEntranceExamUsage, standardized tests such as SAT and ACT]
-
A.
usedByInstitutionType
chosen
Indicates that something (such as a resource, tool, or service) is utilized or employed by a particular type or category of institution.
-
B.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
C.
supportsDiscipline
Indicates that one entity provides assistance, resources, or endorsement that helps sustain or advance a particular discipline.
-
D.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
E.
hasMajorUniversity
Indicates that a location or region contains at least one prominent, large, or academically significant university.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a240b249788190af8dbf7e80e9c91b |
completed | Feb. 28, 2026, 1:11 a.m. |
| PD | Predicate disambiguation | batch_69a23feae8c481908d8c50faac01fc5c |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.